conda | Repository with conda recipes for LAMMPS , GROMACS , etc

I'm trying to study the neural-network-and-deep-learning (http://neuralnetworksanddeeplearning.com/chap1.html). Using the updated version for Python 3 by MichalDanielDobrzanski (https://github.com/MichalDanielDobrzanski/DeepLearningPython). Tried to run it in my command console and it gives an error below. I've tried uninstalling and reinstalling setuptools, theano, and numpy but none have worked thus far. Any help is very appreciated!!

Here's the full error log:

I'm trying to run a SageMaker kernel with Python 3.8 in SageMaker Studio, and the notebook appears to use a separate distribution of Python 3.7. The running app is indicated as tensorflow-2.6-cpu-py38-ubuntu20.04-v1. When I run !python3 -V I get Python 3.8.2. However, the Python instance inside the notebook is different:

Does it make sense to use Conda + Poetry for a Machine Learning project? Allow me to share my (novice) understanding and please correct or enlighten me:

As far as I understand, Conda and Poetry have different purposes but are largely redundant:

• Conda is primarily a environment manager (in fact not necessarily Python), but it can also manage packages and dependencies.
• Poetry is primarily a Python package manager (say, an upgrade of pip), but it can also create and manage Python environments (say, an upgrade of Pyenv).

My idea is to use both and compartmentalize their roles: let Conda be the environment manager and Poetry the package manager. My reasoning is that (it sounds like) Conda is best for managing environments and can be used for compiling and installing non-python packages, especially CUDA drivers (for GPU capability), while Poetry is more powerful than Conda as a Python package manager.

I've managed to make this work fairly easily by using Poetry within a Conda environment. The trick is to not use Poetry to manage the Python environment: I'm not using commands like poetry shell or poetry run, only poetry init, poetry install etc (after activating the Conda environment).

For full disclosure, my environment.yml file (for Conda) looks like this:

For the last 5 days, I am trying to make Keras/Tensorflow packages work in R. I am using RStudio for installation and have used conda, miniconda, virtualenv but it crashes each time in the end. Installing a library should not be a nightmare especially when we are talking about R (one of the best statistical languages) and TensorFlow (one of the best deep learning libraries). Can someone share a reliable way to install Keras/Tensorflow on CentOS 7?

Following are the steps I am using to install tensorflow in RStudio.

Since RStudio simply crashes each time I run tensorflow::tf_config() I have no way to check what is going wrong.

I just downloaded pytube (version 11.0.1) and started with this code snippet from here:

I honestly can't figure out what is happening with this error. I thought it was something in my manifest file but apparently it's not.

Note, this directory is in my Google Drive.

Here is my MANIFEST.in file:

I am trying to install conda on EMR and below is my bootstrap script, it looks like conda is getting installed but it is not getting added to environment variable. When I manually update the $PATH variable on EMR master node, it can identify conda. I want to use conda on Zeppelin.

I also tried adding condig into configuration like below while launching my EMR instance however I still get the below mentioned error.

I am trying to set up a conda environment with python 3.10 installed. For some reason, no install commands for additional packages are working. For example, if I run conda install pandas, I get the error:

I work on a program for two months. Today I suddenly got an error when connecting to the database while using mysql.connector.

Interestingly, this error is not seen when running previous versions.